Can I use this for non-FastAPI projects?

While the scaffolding and routing advice are optimized for FastAPI, the core design principles and Pythonic patterns are applicable to any modern Python application.

How does this skill help with testing?

It provides a standardized 'DataInterfaceStub' strategy, allowing you to test business logic in isolation without requiring a live database connection.

What is the primary architectural flow for this skill?

The skill enforces a strict three-layer dependency flow: Routers (API layer) call Operations (business logic), which then interact with the Database (persistence) via Protocols.

Does this skill require specific dependency injection libraries?

No, it utilizes Python's native 'Protocol' for structural typing and dependency injection, keeping your project lightweight and avoiding vendor lock-in.

Python Clean Architecture

Name: Python Clean Architecture
Author: MKToronto

byMKToronto

•

API Development

Scaffolds, refactors, and reviews Python and FastAPI projects using robust clean architecture and domain-driven design principles.

This skill provides specialized guidance for building maintainable, scalable Python applications with a focus on the FastAPI ecosystem. It implements a strict three-layer architecture (Routers → Operations → Database) and leverages Protocol-based dependency injection to ensure your code remains decoupled and highly testable. Inspired by Arjan Codes, the skill helps developers apply core design principles like high cohesion and low coupling while providing a library of 25+ Pythonic design patterns to resolve common code smells and architectural bottlenecks.

Key Features

01Automated scaffolding for structured FastAPI projects with clear separation of concerns.

023 GitHub stars

03Comprehensive library of Pythonic design patterns including Strategy, Repository, and Unit of Work.

04Intelligent code reviews focused on the seven core design principles of clean architecture.

05Standardized data persistence patterns using DataInterface and DataObject abstractions.

06Protocol-based dependency injection for modular, testable, and decoupled code.

Use Cases

01Implementing complex business logic in 'Operations' layers to keep API routers clean and lean.

02Refactoring tightly coupled legacy Python scripts into a modular, three-layer architecture.

03Bootstrapping a new FastAPI enterprise API with a production-ready folder structure.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add mktoronto/python-clean-architecture clean-architecture

For use in Claude.ai and ChatGPT

Key Features

01Automated scaffolding for structured FastAPI projects with clear separation of concerns.

023 GitHub stars

03Comprehensive library of Pythonic design patterns including Strategy, Repository, and Unit of Work.

04Intelligent code reviews focused on the seven core design principles of clean architecture.

05Standardized data persistence patterns using DataInterface and DataObject abstractions.

06Protocol-based dependency injection for modular, testable, and decoupled code.

Use Cases

01Implementing complex business logic in 'Operations' layers to keep API routers clean and lean.

02Refactoring tightly coupled legacy Python scripts into a modular, three-layer architecture.

03Bootstrapping a new FastAPI enterprise API with a production-ready folder structure.